oapython
oapython is the Python distribution for
OA, a Vulkan 1.4 GPU-first compute,
machine-learning, Vision, Audio, Ui, Plot, Media, and cryptography framework. Install
oapython; import it as oa.
0.7 development preview. The bindings execute real OA C++ objects and Vulkan kernels, but the Python API and binary ABI are not frozen.
Install
python -m pip install oapython
The current wheel targets Linux x86-64, CPython 3.12, and glibc 2.39+. The host must provide a Vulkan loader and a working vendor ICD.
First computation
from oa import *
a = FnMatrix.ones([2, 3])
b = FnMatrix.full([2, 3], 2.0)
c = (a + b) * 0.5
print(FnMatrix.copyToHost(c))
Import is host-only. The first device-backed request creates the native OA host; beginner code does not initialize an engine manually.
Public surface
| Owner | Surface |
|---|---|
Matrix, FnMatrix |
matrices, shapes, dtypes, factories, operators, and numerical operations |
QuantizedMatrix, Quantization |
semantic Q4/Q8 inference weights, pack/dequantize, fused matmul, and .oam persistence |
Module, FnLoss, FnAutograd |
modules, autograd, losses, optimizers, training, and metrics |
Image, FnImage |
image operations and still-image codecs; Vision/Media sessions own video and capture |
Audio, FnAudio |
semantic audio decode/processing operations, GPU saturation/Biquad/SOS filters, and stateful packetization |
plot |
retained figures, Line/Scatter/Bar/Histogram/Heatmap/Image artists, themes, and deterministic image output |
FnHash and Crypto values |
host cryptography and GPU public-data hashing when included in the wheel |
Python uses the same compute graph and kernels as native C++; it is not a NumPy or CPU fallback implementation. Classes use PascalCase and operations use camelCase in both languages, so a Python prototype translates directly to the C++ API. Lowercase domain modules expose the same objects as the root package.
GPU Audio operations use the same public values in Python and C++:
from oa import BiquadCoefficients, FnAudio
audio = FnAudio.decodeFile("input.wav")
section = BiquadCoefficients()
section.b0, section.b1, section.b2 = 0.25, 0.5, 0.25
filtered = FnAudio.sosFilter(audio, [section])
mastered = FnAudio.saturate(filtered, 6.0, 0.5)
FnAudio.saveWavF32("output.wav", mastered)
Core, Ml, Audio, Vision, Plot, end-to-end MNIST, and the canonical 15-workload NLP suite live under
sdk/py/tutorials.
The current desktop matrix and preview-to-preview performance history are published in
the NLP benchmark.
Links
OA is source-available under the Business Source License 1.1 and converts to Apache-2.0 on the Change Date stated in the license.
1 maintainer
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